predictset: Conformal Prediction and Uncertainty Quantification

Implements conformal prediction methods for constructing prediction intervals (regression) and prediction sets (classification) with finite-sample coverage guarantees. Methods include split conformal, 'CV+' and 'Jackknife+' (Barber et al. 2021) <doi:10.1214/20-AOS1965>, 'Conformalized Quantile Regression' (Romano et al. 2019) <doi:10.48550/arXiv.1905.03222>, 'Adaptive Prediction Sets' (Romano, Sesia, Candes 2020) <doi:10.48550/arXiv.2006.02544>, 'Regularized Adaptive Prediction Sets' (Angelopoulos et al. 2021) <doi:10.48550/arXiv.2009.14193>, Mondrian conformal prediction for group-conditional coverage (Vovk, Gammerman, and Shafer 2005) <doi:10.1007/b106715>, weighted conformal prediction for covariate shift (Tibshirani et al. 2019) <doi:10.48550/arXiv.1904.06019>, and adaptive conformal inference for sequential prediction (Gibbs and Candes 2021) <doi:10.48550/arXiv.2106.00170>. All methods are distribution-free and provide calibrated uncertainty quantification without parametric assumptions. Works with any model that can produce predictions from new data, including 'lm', 'glm', 'ranger', 'xgboost', and custom user-defined models.

Version: 0.4.0
Depends: R (≥ 4.1.0)
Imports: cli (≥ 3.6.0), grDevices, graphics, stats
Suggests: testthat (≥ 3.0.0), ranger, ggplot2, knitr, rmarkdown, parsnip (≥ 1.0.0), probably, rsample, workflows
Published: 2026-09-08
DOI: 10.32614/CRAN.package.predictset
Author: Charles Coverdale [aut, cre, cph]
Maintainer: Charles Coverdale <charlesfcoverdale at gmail.com>
BugReports: https://github.com/charlescoverdale/predictset/issues
License: MIT + file LICENSE
URL: https://charlescoverdale.github.io/predictset/, https://github.com/charlescoverdale/predictset
NeedsCompilation: no
Language: en-US
Citation: predictset citation info
Materials: README, NEWS
CRAN checks: predictset results

Documentation:

Reference manual: predictset.html , predictset.pdf
Vignettes: Getting Started with predictset (source, R code)

Downloads:

Package source: predictset_0.4.0.tar.gz
Windows binaries: r-devel: predictset_0.3.0.zip, r-release: predictset_0.4.0.zip, r-oldrel: predictset_0.3.0.zip
macOS binaries: r-release (arm64): predictset_0.3.0.tgz, r-oldrel (arm64): predictset_0.3.0.tgz, r-release (x86_64): predictset_0.4.0.tgz, r-oldrel (x86_64): predictset_0.4.0.tgz
Old sources: predictset archive

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